Computational antitrust tools can help competition authorities in the detection of antitrust infringements. However, these tools require the availability of suitable data sets in order to produce reliable results. In their proof-of-concept study carried out within the realm of the DataComp project, Jan Amthauer, Jürgen Fleiß, Franziska Guggi and Vicky Robertson focus on the area of resale price maintenance. By applying web scraping to price data for washing machines in Austria from a publicly accessible price comparison website, they compiled a comprehensive data set for a period of nearly three months. Visualised with the help of interactive dashboards, this data could then be analysed using various benchmarks in order to determine whether individual washing machine manufacturers and their retailers may be engaging in resale price maintenance. They conclude that the availability of data is a strong driver for research into and the application of computational antitrust tools. If market data were publicly accessible and provided in a more structured format, researchers and competition enforcers could develop ever-more refined computational antitrust applications that would, ultimately, safeguard competition in markets. The paper was just published in the Computer Law & Security Review and is available in open access here.
